Ecological inference techniques: an empirical evaluation using data describing gender and voter turnout at New Zealand elections, 1893–1919
Author
Abstract
Suggested Citation
DOI: 10.1111/j.1467-985X.2009.00609.x
Download full text from publisher
References listed on IDEAS
- Ian Westbrooke & Lisa Jones, 2002. "Applications: Imputation of MĀori Descent for Electoral Calculations in New Zealand," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 44(3), pages 257-265, September.
- Adam N. Glynn & Jon Wakefield & Mark S. Handcock & Thomas S. Richardson, 2008. "Alleviating linear ecological bias and optimal design with subsample data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 179-202, January.
- Nicky Best & Samantha Cockings & James Bennett & Jon Wakefield & Paul Elliott, 2001. "Ecological regression analysis of environmental benzene exposure and childhood leukaemia: sensitivity to data inaccuracies, geographical scale and ecological bias," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 155-174.
- Imai, Kosuke & Lu, Ying & Strauss, Aaron, 2008. "Bayesian and Likelihood Inference for 2 × 2 Ecological Tables: An Incomplete-Data Approach," Political Analysis, Cambridge University Press, vol. 16(1), pages 41-69, January.
- D G Steel & D Holt, 1996. "Rules for Random Aggregation," Environment and Planning A, , vol. 28(6), pages 957-978, June.
- Jon Wakefield, 2004. "Ecological inference for 2 × 2 tables (with discussion)," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 385-445, July.
- M Tranmer & D G Steel, 1998. "Using Census Data to Investigate the Causes of the Ecological Fallacy," Environment and Planning A, , vol. 30(5), pages 817-831, May.
- R. L. Chambers & D. G. Steel, 2001. "Simple methods for ecological inference in 2×2 tables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 175-192.
- Christopher Jackson & And Nicky Best & Sylvia Richardson, 2008. "Hierarchical related regression for combining aggregate and individual data in studies of socio‐economic disease risk factors," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 159-178, January.
- Andrew Gelman & David K. Park & Stephen Ansolabehere & Phillip N. Price & Lorraine C. Minnite, 2001. "Models, assumptions and model checking in ecological regressions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 101-118.
- Jon Wakefield, 2004. "Ecological inference for 2 × 2 tables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 385-425, July.
- Ori Rosen & Wenxin Jiang & Gary King & Martin A. Tanner, 2001. "Bayesian and Frequentist Inference for Ecological Inference: The R×C Case," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 55(2), pages 134-156, July.
- Gary King & Ori Rosen & Martin A. Tanner, 1999. "Binomial-Beta Hierarchical Models for Ecological Inference," Sociological Methods & Research, , vol. 28(1), pages 61-90, August.
- David A. Freedman & Stephen P. Klein & Jerome Sacks & Charles A. Smyth & Charles G. Everett, 1991. "Ecological Regression and Voting Rights," Evaluation Review, , vol. 15(6), pages 673-711, December.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Carolina Plescia & Lorenzo De Sio, 2018. "An evaluation of the performance and suitability of R × C methods for ecological inference with known true values," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 669-683, March.
- Jones, Daniel B. & Troesken, Werner & Walsh, Randall, 2017. "Political participation in a violent society: The impact of lynching on voter turnout in the post-Reconstruction South," Journal of Development Economics, Elsevier, vol. 129(C), pages 29-46.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Rob Eisinga, 2009. "The beta‐binomial convolution model for 2×2 tables with missing cell counts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 24-42, February.
- D. James Greiner & Kevin M. Quinn, 2009. "R×C ecological inference: bounds, correlations, flexibility and transparency of assumptions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 67-81, January.
- Jon Wakefield, 2004. "Ecological inference for 2 × 2 tables (with discussion)," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 385-445, July.
- Puig, Xavier & Ginebra, Josep, 2014. "A cluster analysis of vote transitions," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 328-344.
- Antonio Forcina & Davide Pellegrino, 2019. "Estimation of voter transitions and the ecological fallacy," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1859-1874, July.
- Carolina Plescia & Lorenzo De Sio, 2018. "An evaluation of the performance and suitability of R × C methods for ecological inference with known true values," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 669-683, March.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Zax Jeffrey S., 2012. "Single Regression Estimates of Voting Choices When Turnout is Unknown," Statistics, Politics and Policy, De Gruyter, vol. 4(1), pages 1-22, October.
- Roberto Colombi & Antonio Forcina, 2016. "Latent class models for ecological inference on voters transitions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(4), pages 501-517, November.
- Beh, Eric J., 2010. "The aggregate association index," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1570-1580, June.
- Katherine Wilson & Jon Wakefield, 2022. "A probabilistic model for analyzing summary birth history data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(11), pages 291-344.
- Shuai Shao & Göran Kauermann, 2020. "Understanding price elasticity for airline ancillary services," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(1), pages 74-82, February.
- A. Forcina & M. Gnaldi & B. Bracalente, 2012. "A revised Brown and Payne model of voting behaviour applied to the 2009 elections in Italy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(1), pages 109-119, March.
- Pablo Sandoval & Silvia Ojeda, 2023. "Estimation of electoral volatility parameters employing ecological inference methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 405-426, February.
- Sebastien J.‐P. A. Haneuse & And Jonathan C. Wakefield, 2008. "The combination of ecological and case–control data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 73-93, February.
- Enora Belz & Arthur Charpentier, 2019. "Aggregated Data and Compositional Variables: Methodological Note [Données Agrégées et Variables Compositionnelles : Note Méthodologique]," Working Papers hal-02097031, HAL.
- Sarah Moon, 2024. "Partial Identification of Individual-Level Parameters Using Aggregate Data in a Nonparametric Model," Papers 2403.07236, arXiv.org, revised May 2024.
- Nathan Kallus & Xiaojie Mao & Angela Zhou, 2022. "Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination," Management Science, INFORMS, vol. 68(3), pages 1959-1981, March.
- Arie ten Cate, 2014. "Maximum likelihood estimation of the Markov chain model with macro data and the ecological inference model," CPB Discussion Paper 284.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
- Gillian A. Lancaster & Mick Green & Steven Lane, 2006. "Reducing bias in ecological studies: an evaluation of different methodologies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 681-700, October.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssa:v:173:y:2010:i:1:p:185-213. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.